DBMS > Amazon DynamoDB vs. Blazegraph vs. FatDB vs. IRONdb vs. jBASE

System Properties Comparison Amazon DynamoDB vs. Blazegraph vs. FatDB vs. IRONdb vs. jBASE

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

A robust multi-value DBMS comprising development tools and middleware

Primary database model

Document store
Key-value store

Graph DBMS
RDF store

Document store
Key-value store

Time Series DBMS

Multivalue DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.75
Rank	#219	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Website

aws.amazon.com/dynamodb

blazegraph.com

www.circonus.com/solutions/time-series-database/

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

Technical documentation

docs.aws.amazon.com/dynamodb

wiki.blazegraph.com

docs.circonus.com/irondb/category/getting-started

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

Developer

Amazon

Blazegraph

FatCloud

Circonus LLC.

Rocket Software (formerly Zumasys)

Initial release

2012

2006

2012

2017

1991

Current release

2.1.5, March 2019

V0.10.20, January 2018

5.7

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

extended commercial license available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

Server operating systems

hosted

Linux
OS X
Windows

Windows

Linux

AIX
Linux
Windows

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

RDF literal types

yes

text, numeric, histograms

optional

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

Via inetgration in SQL Server

SQL-like query language (Circonus Analytics Query Language: CAQL)

Embedded SQL for jBASE in BASIC

APIs and other access methods

RESTful HTTP API

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
Basic
Jabbascript
Java

Server-side scripts

Stored procedures

yes

via applications

yes, in Lua

yes

Triggers

yes

by integration with AWS Lambda

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

configurable replication factor, datacenter aware

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

yes

Relationships in Graphs

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

ACID across one or more tables within a single AWS account and region

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Security and Authentication via Web Application Container (Tomcat, Jetty)

Can implement custom security layer via applications

Access rights can be defined down to the item level

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